Correlation and path analysis studies for yield in tomato (Solanum lycopersicum L.)

Correlation and path analysis were carried out in forty-five tomato hybrids along with ten parents for yield. The association studies showed that fruit yield per plant was positively and significantly correlated with average fruit weight. However, fruit yield per plant was negatively correlated with number of cluster per plant, length of fruits, total number of branches per plant, TSS and ascorbic acid content of fruit. Path analysis studies done to study the cause and effect relationship revealed that number of flowers per cluster, number of fruits per cluster, number of fruits per plant, number of locules per fruit and average fruit weight had high positive direct effects on fruit yield per plant. Hence, direct selection for these traits is done for improving fruit yield per plant.

Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume Number 09 (2019) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2019.809.059 Correlation and Path Analysis Studies for Yield in Tomato (Solanum lycopersicum L.) Archana Mishra1*, A Nandi2, A.K Das1, S Das2, I.C Mohanty3, S.K Pattanayak4, G.S Sahu1 and P Tripathy1 Department of Vegetable Science, 3Department of Agricultural Biotechnology, Department of Soil Science and Agricultural Chemistry, College of Agriculture, Odisha University of Agriculture and Technology, Bhubaneswar, India AICRP on Vegetable Crops, Directorate of Research, Odisha University of Agriculture and Technology, Bhubaneswar, India *Corresponding author ABSTRACT Keywords Correlation and Path analysis, Tomato, Genotypes and Yield Article Info Accepted: 04 August 2019 Available Online: 10 September 2019 Correlation and path analysis were carried out in forty-five tomato hybrids along with ten parents for yield The association studies showed that fruit yield per plant was positively and significantly correlated with average fruit weight However, fruit yield per plant was negatively correlated with number of cluster per plant, length of fruits, total number of branches per plant, TSS and ascorbic acid content of fruit Path analysis studies done to study the cause and effect relationship revealed that number of flowers per cluster, number of fruits per cluster, number of fruits per plant, number of locules per fruit and average fruit weight had high positive direct effects on fruit yield per plant Hence, direct selection for these traits is done for improving fruit yield per plant Introduction Tomato (Solanum lycopersicum L.) is a member of the family solanaceae and significant warm season fruit vegetable crop of special economic importance in the horticultural industry worldwide (He et al., 2003) Tomato is a native of Peru Equador region (Rick, 1969) and having chromosome number 2n=24 Tomato is the most important vegetable crop next only to potato because of its high yielding potential, wider adaptability and multipurpose uses It is widely consumed vegetable crop throughout the world both for fresh fruit market and the processed food industry It is grown at farm and kitchen garden for slice, soup, sauce, ketchup, cooked vegetable etc It is a rich source of vitamins A, B and C Tomato is grown as an annual or short lived perennial herbaceous plants It has taproot and growth habit of the plant is determinate, semi-determinate and 489 Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 indeterminate Yield is a complex character and selection for yield and yield components deserves considerable attention A crop breeding programme, aimed at increasing the plant productivity requires consideration not only of yield but also of its components that have direct or indirect effect on yield Correlation and path coefficient analysis give an insight into the genetic variability present in populations Correlation coefficient analysis measures the mutual relationship between various plant characters and determines the component characters on which selection can be based for improvement in yield Path analysis splits the correlation coefficients into direct and indirect effects of a set of dependent variables on the independent variable thereby aids in selection of elite genotype An improvement in yield in self pollinated crop like tomato is normally achieved by selecting the genotypes with desirable character combinations existing in nature or by hybridization Information on the nature and extent of variability present in genetic stocks, heritability, genetic advance and interrelationship among various characters is a prerequisite for framing any selection program The present study was carried out to get the information for character association for yield in fifty-five genotypes of tomato Materials and Methods Fifty-five genotypes of tomato consisting of 45 F1 hybrids and 10 parents were evaluated in a randomized block design with two replications at Department of Vegetable Science, College of Agriculture, Orissa University of Agriculture and Technology, Bhubaneswar Seeds sowing in the nursery beds was carried out on October 9th and transplanting was done on 8th November, 2016 All recommended cultural practices were followed to raise good crop stand and growth of the plants The observation were recorded on five randomly selected plants per replication for each germplasm on eighteen different characters: days to 1st flowering, days to 50% flowering, number of cluster per plant, number of flowers per cluster, number of fruits per cluster, number of fruits per plant, length of fruits, diameter of fruits, pericarp thickness, number of locules per fruit, plant height, total number of branches, average fruit weight, yield per plant, total yield per plot, TSS, acidity content of fruit and ascorbic acid content of fruit The correlations of coefficients among yield and quality attributes were calculated as suggested by Panse and Sukhatme (1985) Path coefficient analysis was carried out according to Dewey and Lu (1959) Results and Discussion The mean value for yield per plant of the genotypes revealed that the highest value being shown by BT-22-4-1 (2.565) followed by BT-22-4-1 X BT-3 (2.495), BT-22-4-1 X BT-17-2 (2.405), BT-19-1-1-1 X BT-22-4-1 (2.105) and the lowest value possess by BT-1 X BT-22-4-1 (0.165) followed by Utkal Kumari X BT-19-1-1-1 (0.570), BT-1 (0.740) and BT-1 X Utkal Kumari (0.750) (Table 1) The range for yield per plant of tomato genotypes under study is (0.165-2.565) Simple correlation studies were carried for all the characters studied The degree of association between fruit yield and its contribution can be estimated by correlation coefficient at genotypic and phenotypic levels All possible phenotypic and genotypic correlation coefficient between fruit yield and its components was calculated and is given in (Tables and 3) For most of the characters genotypic correlation coefficient was found higher than phenotypic correlation coefficient indicating a strong inherent association among various characters Similar findings were observed by Mohanty (2003) and Singh 490 Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 (2009) Average fruit weight had significant positive correlation with fruit yield per plant The results are in accordance with Kumar et al., (2006) for average fruit weight The genotypic association of days to 50% flowering showed significant positive association with length of fruits Similarly a significant and positive correlation of number of flowers per cluster was found with number of fruits per cluster, number of locules per fruit, plant height and average fruit weight while diameter of fruits was found to be in positive and significant association with number of locules per fruit Results are in accordance with Singh (2009) and Ara et al., (2009) Days to first flowering and days to 50% flowering showed significant negative association with number of flowers per cluster Similarly number of cluster per plant exhibited negative significant association with average fruit weight and positively correlated with number of flowers per cluster, number of fruits per plant, number of locules per fruit, total number of branches per plant, TSS and ascorbic acid content while number of flowers per cluster had negative significant correlation with diameter of fruits and positive association with length of fruits, pericarp thickness, total number of branches per plant, TSS, ascorbic acid and acidity content Number of fruits per plant showed significant negative association with plant height while positively correlated with length and diameter of fruits, pericarp thickness, total number of branches per plant, TSS and ascorbic acid content Same observations were made by Singh et al., (2007) and Singh (2009) for number of fruits per plant The phenotypic association of days to 50% flowering exhibited significant positive correlation with days to 50% flowering while number of flowers per cluster showed the same with number of fruits per cluster The results observed are similar to the findings of Dhankar and Dhankar (2006) Yield per plant had positive association with days to first flowering, days to 50% flowering, number of flowers per cluster, number of fruits per cluster, number of fruits per plant, diameter of fruits, pericarp thickness, number of locules per fruit, plant height and acidity content while had negative association with number of cluster per plant, length of fruits, total number of branches per plant, TSS and ascorbic acid content Similar results for some characters are also observed by Prashanth et al., (2008) Average fruit weight had positive association with days to first flowering, days to 50% flowering number of fruits per cluster, plant height, TSS and acidity content while had negative association with ascorbic acid acid content, fruit length and pericarp thickness Results are in accordance with Kumar and Dudi (2011) TSS had positive association acidity content while negatively correlated with ascorbic acid content Ascorbic acid had negative association with TSS Results are in accordance with Kumar and Dudi (2011) for fruit weight, TSS, acidity The path coefficient studies (Table 4) revealed that plant number of fruits per cluster, number of flowers per cluster, number of fruits per plant, average fruit weight and number of locules per fruit had high positive direct effects on fruit yield per plant while days to first flowering, days to 50% flowering, fruit diameter, pericarp thickness and plant height had moderate direct positive effects on fruit yield per plant High negative direct effects on fruit yield per plant had been observed for number of cluster per plant, fruit length, total number of branches per plant, TSS, ascorbic acid and acidity content The results are in accordance with the findings of Asati et al., (2008) for plant height, number of primary branches per plant, days to 50% flowering and fruit weight, Kumar and Thakur (2007) for number of fruits per plant, fruit length and fruit width 491 Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 Table.1 Mean of 45 F1 hybrids and 10 parent GENOTYPES YIELD PLANT- V28 V29 V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21 V22 V23 V24 V25 V26 V27 Bt-1 x Utkal Dipti BT-1 x Utkal Kumari BT-1 x BT-19-1-1-1 BT-1 x BT-317 BT-1 x BT-22-4-1 BT-1 x BT-3 BT-1 x BT-17-2 BT-1 x BT-507-2-2 BT-1 x BT-21 Utkal Dipti x Utkal Kumari Utkal Dipti x BT-19-1-1-1 Utkal Dipti x BT-317 Utkal Dipti x BT-22-4-1 Utkal Dipti x BT-3 Utkal Dipti x BT-17-2 Utkal Dipti x BT-507-2-2 Utkal Dipti x BT-21 Utkal Kumari x Bt-19-11-1 Utkal Kumari x BT-317 Utkal Kumari x BT-22-41 Utkal Kumari x BT-3 Utkal Kumari x BT-17-2 Utkal Kumari x BT-5072-2 Utkal Kumari x BT-21 BT-19-1-1-1 x Bt-317 BT-19-1-1-1 x BT-22-4-1 BT-19-1-1-1 x BT-3 1.045 0.750 1.095 0.965 0.165 1.495 1.450 1.195 1.310 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40 V41 V42 V43 V44 V45 V46 V47 V48 V49 V50 V51 V52 V53 V54 V55 SED CD 0.850 1.185 1.060 2.050 1.350 1.295 1.030 1.085 0.570 0.840 1.490 1.160 1.095 1.000 1.180 0.840 2.105 1.205 492 BT-19-1-1-1 x BT-17-2 BT-19-1-1-1 x BT-507-22 BT-19-1-1-1 x BT-21 BT-317 x BT-22-4-1 BT-317 x BT-3 BT-317 x BT-17-2 BT-317 x BT-507-2-2 BT-317 x BT-21 BT-22-4-1 x BT-3 BT-22-4-1 x BT-17-2 BT-22-4-1 x BT-507-2-2 BT-22-4-1 x BT-21 BT-3 x BT-17-2 BT-3 x BT-507-2-2 BT-3 x BT-21 BT-17-2 x Bt-507-2-2 BT-17-2 x BT-21 BT-507-2-2 x Bt-21 BT-1 Utkal Dipti Utkal Kumari BT-19-1-1-1 BT-317 BT-22-4-1 BT-3 BT-17-2 BT-507-2-2 BT-21 1.295 1.385 1.170 1.215 1.685 1.410 1.340 1.015 2.495 2.405 2.060 2.030 1.470 1.380 1.255 1.370 1.310 1.190 0.740 0.935 0.645 1.095 0.920 2.565 1.640 1.485 1.305 1.245 0.129 0.259 Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 Table.2 Genotypic correlation co-efficient (rg) between all pairs of 17 characters in tomato Characters Days to 1st flowering Days to 50% flowering No of cluster/plant No of flowers/clust er No of fruits/cluste r No of fruits/plant Length of fruits Diameter of fruits Pericarp thickness of fruit No of locules/fruit Plant height r Days to 50% flowering No of cluster/ plant No of flowers/ cluster No of fruits/ cluster No of fruits/ plant Length of fruits Diamete r of fruits -1.13902 -0.13042 -0.55081* -0.12662 -0.12649 0.18004 0.14443 Pericar p thickne ss of fruit 0.15133 No of locules/ fruit Plant height Total no of branche s/plant Average fruit weight 0.24604 -0.14160 -0.23246 0.07171 -0.12566 Ascorbi c acid content Acidity content of fruit Yield/pla nt 0.10602 -0.00138 0.07610 0.28786 0.00796 0.03787 -0.53999* -0.36075 -0.23321 0.43270* -0.26021 0.31008 0.21120 0.12395 0.03145 0.17267 -0.10335 0.15076 0.05652 -0.23688 0.31040 -0.38789 -0.03499 -0.11355 0.13793 -0.08923 0.34211 -0.56164** 0.02640 0.22117 -0.08670 -0.15970 0.94951** -0.11423 0.21809 -0.42677* 0.14487 0.47090* 0.44999* 0.03456 0.43973* 0.02791 0.31150 0.33475 0.00829 0.10521 0.08859 0.07006 0.20141 0.24927 0.14150 0.11603 0.31234 0.14567 0.18517 0.16359 0.08529 0.00243 0.31796 0.08001 -0.23759 -0.44357* 0.16651 -0.24369 0.35606 0.10862 -0.37518 0.06112 0.04681 0.03726 0.19970 0.12739 0.23145 -0.11100 -0.06624 0.02345 -0.23074 -0.21288 0.37177 0.44738* 0.02603 -0.26310 0.15640 0.32378 -0.05490 0.28049 0.15579 0.20180 0.09222 -0.17705 -0.05846 0.06433 0.21047 -0.04285 0.04832 -0.13084 0.08563 0.16743 0.17371 0.20413 0.16727 0.08167 -0.00519 0.12786 0.04462 -0.13453 0.02455 0.05085 -0.36245 0.19290 -0.15940 -0.35047 -0.40893 -0.04071 -0.13416 0.22108 0.64190** -0.23596 0.15194 -0.02976 -0.05970 -0.33896 g r TSS of fruit g r g r g r g r g r g r g r g r g r g Total no of branches/pl ant Average fruit weight TSS of fruit r g r g r g Ascorbic acid content Acidity content of fruit r g r 0.13356 g *and ** indicates significant at and percent level, respectively 493 Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 Table.3 Phenotypic correlation co-efficient (rp) between all pairs of 17 characters in tomato Characters Days to 1st flowering Days to 50% flowering No of cluster/plant No of flowers/cluste r No of fruits/cluster No of fruits/plant Length of fruits Diameter of fruits Pericarp thickness of fruit No of locules/fruit Plant height Total no of branches/plan t Average fruit weight TSS of fruit Ascorbic acid content Acidity content of fruit rp rp rp rp Days to 50% flowerin g No of cluster/pla nt No of flowers/ cluster No of fruits/ cluster No of fruits/ plant Length of fruits Diamete r of fruits 0.594** -0.081 0.099 0.148 0.107 -0.163 -0.104 0.226 0.158 0.109 -0.054 -0.105 0.818** rp rp rp rp No of locules/ fruit Plant height Total no of branche s/plant Average fruit weight TSS of fruit Ascorbic acid content Acidity content of fruit Yield/plant -0.047 Pericar p thicknes s of fruit 0.091 -0.003 -0.008 -0.291 0.056 -0.094 0.066 0.046 0.104 -0.093 -0.016 0.182 -0.100 -0.017 -0.130 0.097 0.048 0.150 -0.003 0.040 0.218 -0.164 -0.094 -0.040 0.091 -0.052 0.208 -0.401 0.053 0.163 -0.092 -0.084 -0.025 0.081 0.123 0.069 -0.183 0.056 -0.007 0.127 0.035 0.089 0.036 0.010 0.041 0.047 0.198 0.048 -0.106 0.101 0.072 0.178 0.100 0.103 0.067 0.049 -0.066 0.143 0.035 -0.082 -0.232 0.104 -0.150 0.285 0.088 -0.313 0.082 -0.004 0.036 0.069 -0.008 0.139 -0.133 -0.017 0.012 -0.139 -0.184 0.172 0.090 -0.069 -0.069 0.021 0.156 -0.022 0.170 0.052 0.062 -0.019 -0.166 -0.049 0.063 0.172 -0.040 0.039 -0.006 0.062 0.120 0.120 0.140 0.153 0.065 0.034 0.102 -0.262 0.014 0.141 -0.102 -0.122 0.050 -0.253 0.005 -0.281 0.038 -0.128 0.175 0.600** 0.230 -0.148 -0.056 -0.022 -0.326 rp rp rp rp rp rp rp rp 0.098 *and ** indicates significant at and percent level, respectively 494 Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 Table.4 Estimate of direct (diagonal) and indirect effect of component characters on yield in tomato Characters Days to 1st flowering Days to 50% flowering No.of cluster/plant No.of flowers/cluster No.of fruits/cluster No.of fruits/plant Length of fruits Diameter of fruits Pericarp thickness of fruit No.of locules/fruit Plant height Total no.of branches/plant Average fruit weight TSS of fruit Ascorbic acid content Acidity content of fruit Days to Days to 1st 50% flowering flowering No.of cluster/ plant No.of flowers/ cluster No.of fruits/ cluster No.of fruits/ plant Length of Diameter fruits of fruits 0.04121 0.21097 0.06469 -0.33001 0.10759 -0.07398 -0.07424 0.00176 0.01547 0.08842 -0.00604 0.01598 0.02811 0.01482 -0.02873 0.00007 Genotypic correlatio n with Yield /plant 0.07610 0.04694 0.18522 0.06233 -0.32352 0.30653 -0.13640 -0.17842 -0.00318 0.03171 0.07590 0.00529 -0.00216 0.06767 -0.02161 -0.07800 -0.00043 0.03787 0.00537 0.02328 -0.49602 0.03386 0.20128 0.18154 0.15994 -0.00043 -0.01161 0.04957 -0.00381 -0.02352 -0.22013 -0.00378 -0.05993 0.00470 -0.15970 0.02270 0.10002 -0.02804 0.59913 -0.80681 -0.06681 -0.08993 -0.00521 0.01481 0.16922 0.01920 -0.00238 0.17235 -0.00400 -0.08441 -0.01814 0.00829 0.00522 0.06682 0.11750 0.56888 0.84971 0.06154 -0.03653 0.00086 0.02060 0.08958 0.00604 -0.00798 0.12242 -0.02088 -0.05018 -0.00886 0.08529 0.00521 -0.00742 -0.00595 -0.00624 0.04320 -0.08014 0.04820 -0.05743 -0.15397 0.19240 0.01736 0.05632 -0.06844 0.13066 -0.25569 0.08680 -0.08940 -0.07528 -0.05953 -0.17114 0.58487 0.00142 0.18596 0.04679 -0.00100 -0.41234 -0.01930 -0.01536 0.00388 0.00057 0.01221 0.00454 0.00818 0.00381 0.03802 0.10226 -0.08538 0.07176 0.16077 0.07252 -0.01893 0.00544 0.00111 0.00394 -0.01145 -0.01591 0.01809 0.01217 -0.09551 -0.04351 0.06130 -0.02291 -0.05104 0.00949 -0.04641 -0.00922 -0.02943 -0.00635 0.01488 -0.05703 0.02033 0.01250 -0.01520 0.00232 0.06112 -0.21288 0.15579 0.04832 -0.01014 0.00584 0.00958 -0.03912 -0.02296 -0.00583 -0.06841 0.04426 -0.16970 0.28213 0.26960 0.02070 -0.21181 -0.12023 -0.09859 -0.13896 -0.25943 0.09738 -0.08235 -0.05253 -0.09543 0.00546 0.00032 -0.00321 0.02063 0.00943 -0.01810 0.35936 -0.04702 0.03077 -0.00558 0.04267 -0.00022 -0.00589 0.00036 -0.06876 0.06562 0.05011 -0.14206 -0.02490 -0.00640 -0.02765 -0.05531 0.03645 -0.00906 -0.00133 0.01899 0.08167 0.05085 -0.40893 -0.00296 -0.03198 0.27859 0.26346 -0.26540 -0.14252 0.04577 0.00191 -0.00598 0.06017 0.00546 0.02492 0.39194 -0.00584 0.04319 0.03635 -0.01198 0.64190 0.00426 -0.00437 -0.02792 -0.05332 -0.01310 -0.10971 0.01672 0.18663 -0.12378 -0.15734 0.20825 0.06353 0.02731 -0.00967 0.00395 -0.00067 0.00658 0.02152 0.06242 0.07336 0.00190 -0.00574 -0.01326 0.01096 0.01596 -0.05258 -0.14335 -0.03382 -0.06394 -0.27098 0.00823 0.00324 -0.02976 -0.33896 0.00006 -0.00147 0.04300 0.20056 -0.13901 -0.21943 0.09514 0.00342 -0.00438 0.06011 0.00105 0.02410 0.08665 0.02178 0.01618 -0.05419 0.13356 Residual effect = 0.6944423 Figures underlined denoted the Direct Effect 495 Pericarp thickness of fruit No of locules/ fruit Plant height Total no of branche s/plant Average fruit weight TSS of fruit Ascorbi c acid content Acidity content of fruit Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 simple sequence repeat (SSR) markers and their use in determining relationships among Lycopersicon esculentum cultivars Theoretical Applied Genetics, 106: 363-373 Kumar, M and Dudi, B.S (2011) Study of correlation for yield and quality characters in tomato (Lycopersicon esculentum Mill.) Electronic Journal of Plant Breeding, 2(3): 453-460 Kumar, R and Thakur, M.C (2007) Genetic variability, heritability, genetic advance, correlation coefficient and path analysis in tomato Haryana Journal of Horticultural Science, 36(3 & 4): 370373 Kumar, R., Niraj Kumar, Jagadeesh Singh and Rai, G.K (2006) Studies on yield and quality traits in tomato Vegetable Science, 33(2): 126-132 Mohanty BK (2003) Variability, heritability, correlation and path coefficient studies in tomato Indian Journal of Agricultural Research, 37(1): 68-71 Panse VG, Sukhatme PV (1985) Statistical Methods for Agricultural Workers (2nd Edn.), Indian Council of Agricultural Research, New Delhi, 381 Prashanth, S.J., Jaiprakashnarayan, R.P., Mulge, R and Madalageri, M.B (2008) Correlation and path analysis in tomato (Lycopersicon esculentum Mill.) The Asian Journal of Horticulture, 3(2): 403-408 Rick C M (1969) Origin of cultivated tomato, current status and the problem International Botanical Congress, 180p Singh AK (2009) Genetic variability, heritability and genetic advance studies in tomato under cold arid region of Ladakh Indian Journal of Horticulture 66(3): 400-403 Singh, J., Mathura Rai, Rajesh Kumar, Prasanna, H.C., Ajay Verma Rai, G.K and Singh, A.K (2007) Genotypic variation and hierarchical clustering of Acknowledgement This research was supported/partially supported by Department of Vegetable Science, College of Agriculture, OUAT, Bhubaneswar and DST, Government of India We thank our colleagues from Odisha University of Agriculture and Technology who provided insight and expertise that greatly assisted the research, although they may not agree with all of the interpretations/conclusions of this paper We would also like to show our gratitude to the Professors of Department of Agricultural Biotechnology and Department of Soil Science and Agricultural Chemistry, College of Agriculture, OUAT, Bhubaneswar for sharing their pearls of wisdom with us during the course of this research We are also immensely grateful to the workers of AICRP on Vegetable Crops, Directorate of Research, OUAT, Bhubaneswar References Ara A, Narayan R, Ahmed N and Khan SH (2009) Genetic variability and selection parameters for yield and quality attributes in tomato Indian Journal of Horticulture 3(2): 222 225 Asati, B.S., Rai, N and Singh, A.K (2008) Genetic parameters study for yield and quality traits in tomato The Asian Journal of Horticulture, 3(2): 222-225 Dewey DR, Lu KH (1959) A correlation and path co-efficient analysis of components of crested wheat grass seed production Agronomy Journal, 51(9):515-518 Dhankhar, S.K and Dhankar, S.S (2006) Variability, heritability, correlation and path coefficient studies in tomato Haryana Journal of Hortcultural Science, 35(1&2): 179-181 He, C., Poysa, V and Yu, K (2003) Development and characterization of 496 Int.J.Curr.Microbiol.App.Sci (2019) 8(9): 489-497 tomato (Solanum lycopersicum) based on morphological and biochemical traits, Vegetable Science 34(1): 40-45 How to cite this article: Archana Mishra, A Nandi, A.K Das, S Das, I.C Mohanty, S.K Pattanayak, G.S Sahu and Tripathy, P 2019 Correlation and Path Analysis Studies for Yield in Tomato (Solanum lycopersicum L.) Int.J.Curr.Microbiol.App.Sci 8(09): 489-497 doi: https://doi.org/10.20546/ijcmas.2019.809.059 497 ... Archana Mishra, A Nandi, A.K Das, S Das, I.C Mohanty, S.K Pattanayak, G.S Sahu and Tripathy, P 2019 Correlation and Path Analysis Studies for Yield in Tomato (Solanum lycopersicum L.) Int.J.Curr.Microbiol.App.Sci... improvement in yield in self pollinated crop like tomato is normally achieved by selecting the genotypes with desirable character combinations existing in nature or by hybridization Information... out to get the information for character association for yield in fifty-five genotypes of tomato Materials and Methods Fifty-five genotypes of tomato consisting of 45 F1 hybrids and 10 parents